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EURAXESS

MSCA-COFUND-CLEAR-Doc - PhD Position #CD22-56: Optimization and stochastic approaches based on electrical resistivity data sets for monitoring reinforced concrete structures

13/10/2022

Job Information

Organisation/Company
Université Gustave Eiffel
Department
MAST-LAMES
Research Field
Mathematics
Physics
Engineering
Engineering » Civil engineering
Researcher Profile
First Stage Researcher (R1)
Country
France
Application Deadline
Type of Contract
Temporary
Job Status
Full-time
Hours Per Week
35
Is the job funded through the EU Research Framework Programme?
H2020 / Marie Skłodowska-Curie Actions COFUND
Marie Curie Grant Agreement Number
101034248
Is the Job related to staff position within a Research Infrastructure?
No

Offer Description

This PhD topic aims at contributing to sustainable development by developing new and instrumented infrastructures and by helping the management of aged assets that need to be maintained and to save resources. In the aim to manage reinforced concrete assets that constitute transportation infrastructures for people, goods and energy for tomorrow’s cities, structural health monitoring systems need to be built that can be used in a broad variety of environmental conditions. Indeed, in the context of global warming, an increasing number of major existing reinforced concrete structures included in large European harbours, presently emerged or in the tidal zone, may be subjected to temporary immersion.

Water content in cover concrete is one of the main parameters governing long term durability of reinforced concrete structures. This state parameter most particularly influences the ingress of aggressive agents that can change concrete pH and initiate rebar corrosion. This PhD focuses on water transfer and the penetration of chloride ions that are harmful to rebars and that are highly concentrated in marine environments or de-icing salts. The early detection of such moisture and chloride ingress in a non-destructive manner and the monitoring of changes in the corresponding profiles are of utmost importance for enabling the diagnosis of possible corrosion pathologies and to forecast their evolution.

 

In porous materials, DC-electrical resistivity is a property that is highly sensitive to water content and ionic content, particularly chloride content. Recent works [Fares et al. 2018, Fargier et al. 2021] have shown that water saturation profiles as function of depth could be estimated from surface measurements, which measure so-called apparent resistivity values for several electrode configurations, possibly combined with capacitive measurements [AlHajj et al. 2021]. The inverse problem, however, severely lacks information: only few data are available for each acquisition sequence and data suffer from high uncertainty, partly due to their sensitivity to uncertainties in the positioning of the sensor, the electrical coupling between electrodes and concrete surface and the intrinsic loss of resolution with depth. Satisfactory results were obtained by strongly constraining the searched profiles via parametric models with a very small number of degrees of freedom, which rather accurately describe simple profiles corresponding to either to drying or to penetration of water or aggressive agents through diffusion or imbibition [Alhajj et al. 2021]. However, such constraints strongly limit the inspection to the case of monotonic profiles. Yet, some natural cyclic phenomena lead to non-monotonic profiles, as for example chloride profiles in tidal range zones. Therefore, more general models need to be investigated.

Thus, this PhD project aims at extending the monitoring capabilities to a wider range of environmental conditions, in an effort to anticipate consequences of climate change, by developing an inversion methodology that enables the estimation of a higher diversity of water saturation profile shapes. Such a methodology will rely on the acquisition of larger datasets and of higher quality, to enable a continuous structural health monitoring of instrumented assets exposed to harsh conditions and that exhibit property profiles of higher complexity.

 

From the experimental side, this thesis will implement a new acquisition system relying on the permanent incorporation of sensors into the surface of a concrete slab. We have indeed developed multi-electrode resistivity sensors to be embedded in old or recent reinforced concrete structures in various environmental conditions. Being fixed, such sensors will prove apparent resistivity measurements continuously, with much more reproducibility than current measurement setups, and less subject to the electrical coupling between each pair of sensors. At the beginning of the thesis, an already existing reinforced concrete structure will be equipped and similar sensors will be cast in fresh slabs, that will then be subjected to different type of constraints and monitored during approximately 2.5 years. Indeed, building the required data base is necessary to the validation of the developed methodology. Since calibration curves that link the resistivity to the water or chloride content are known for this particular concrete formulation, standard tests will be performed in order to validate the water / chloride profiles obtained by inversion.

From the methodological side, the inversion problem will be tackled by considering a non-parametric model for the water saturation profile, where profile is discretized into a large number of unknown values along the depth axis, then enabling the fitting of arbitrary profile shapes to the data. Since the resulting high-dimensional estimation problem may be ill-posed, regularization approaches will be developed in order to incorporate weak prior information on the searched profile, such as smoothness and boundedness, and even time continuity between successive inspections. A dedicated optimization algorithm will be developed for computing the solution, e.g. based on gradient descent methods. Specific care will be taken on the efficient and fast evaluation of the forward model, that links the unknown discretized profile to the corresponding predicted data by solving (numerically and partially analytically) the corresponding electrical equations. Additionally, the inverse problem will also be addressed within the Bayesian framework, where statistical estimation based on Markov Chain Monte-Carlo methods should provide uncertainty confidence intervals on the estimated profiles, which is crucial information for monitoring critical structures.

The Early Stage Researcher (ESR) shall be supervised by a local team of researchers that are acknowledged at an international level and are used to collaborate. The ESR will also have the opportunity to do some networking and build collaboration during her/his 3-month internship in a foreign laboratory. Several possible foreign laboratories are considered, the choice will be done with the ESR.

Fares M., Villain G., Bonnet S., Palma Lopes S., Thauvin B., Thiéry M., Determining chloride content profiles in concrete using a resistivity probe, Cement and Concrete Composites, 2018(94): 15-326 https://doi.org/10.1016/j.cemconcomp.2018.08.001

Fargier Y., Villain G., Palma Lopes S., Fares M., Optimized Retrieval of water content profiles in cover concrete by means of ERT, Journal of Applied Geophysics, 2021(193), art. no.104413, https://doi.org/10.1016/j.jappgeo.2021.104413

Alhajj, M.A., Bourguignon, S., Palma-Lopes, S., Villain, G., Joint inversion of electromagnetic measurements for the determination of water saturation profiles in concrete structures, Cement and Concrete Research, 2021(147), art. no.106500, https://doi.org/10.1016/j.cemconres.2021.106500

Requirements

Research Field
Engineering
Education Level
Bachelor Degree or equivalent
Skills/Qualifications
  • At the time of the deadline, applicants must be in possession or finalizing their Master’s degree or equivalent/postgraduate degree.
  • At the time of recruitment, applicants must be in possession of their Master’s degree or equivalent/postgraduate degree which would formally entitle to embark on a doctorate.
Languages
ENGLISH
Level
Basic
Languages
FRENCH
Level
Excellent

Additional Information

Benefits
  • High-quality doctoral training rewarded by a PhD degree, delivered by Université Gustave Eiffel
  • Access to cutting-edge infrastructures for research & innovation.
  • Appointment for a period of 36 months based on a salary of 2 700 € (gross salary per month).
  • Job contract under the French labour legislation in force, respecting health and safety, and social security: 35 hours per week contract, 25 days of annual leave per year.
  • International mobility will be mandatory
  • An international environment supported by the adherence to the European Charter & Code.
  • Access to dedicated CLEAR-Doc trainings with a strong interdisciplinary focus, together with a Career development Plan.
Eligibility criteria

Applicants must fulfil the following eligibility criteria:

  • At the time of the deadline, applicants must be in possession or finalizing their Master’s degree or equivalent/postgraduate degree.
  • At the time of recruitment, applicants must be in possession of their Master’s degree or equivalent/postgraduate degree which would formally entitle to embark on a doctorate.
  • At the time of the deadline, applicants must be in the first four years (full-time equivalent research experience) of their research career (career breaks excluded) and not yet been awarded a doctoral degree. Career breaks refer to periods of time where the candidate was not active in research, regardless of his/her employment status (sick leave, maternity leave etc). Short stays such as holidays and/or compulsory national service are not taken into account.
  • At the time of the deadline, applicants must fulfil the transnational mobility rule: incoming applicants must not have resided or carried out their main activity (work, studies, etc.) in France for more than 12 months in the 3 previous years.

One application per call per year is allowed.

Applicants must be available full-time to start the programme on schedule (November 1st 2023).

Application rules are enforced by the French doctoral system which specifies a standard duration of 3 years for a full-time PhD together with the MSCA standards and the OTM-R European rules as follows.

Citizens of any nationality may apply to the programme.

There is no age limit.

Selection process

Please refer to the Guide for Applicants available on the CLEAR-Doc website.

Additional comments
  • The First step before applying is contacting the PhD supervisor. You will not be able to apply without an acceptation letter from the PhD supervisor.
  • International Mobility: Please contact the PhD supervisor for any additional detail on job offer and the international Mobility
  • Please contact the PhD supervisor for any additional detail on job offer.
  • There are no restrictions concerning the age, gender or nationality of the candidates. Applicants with career breaks or variations in the chronological sequence of their career, with mobility experience or with interdisciplinary background or private sector experience are welcome to apply.
  • Support service is available during every step of the application process by email: clear-doc@univ-eiffel.fr
Website for additional job details

Work Location(s)

Number of offers available
1
Company/Institute
Université Gustave Eiffel
Country
France
State/Province
Loire Atlantique
City
Bouguenais
Postal Code
44340
Street
Allée des Ponts et Chaussées
Geofield

Contact

City
Marne-La-Vallée
Website
Street
5, Boulevard Descartes
Postal Code
77454
E-Mail
geraldine.villain@univ-eiffel.fr